{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "from pandas import Series,DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Python</th>\n",
       "      <th>En</th>\n",
       "      <th>Math</th>\n",
       "      <th>Physic</th>\n",
       "      <th>Chem</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>122</td>\n",
       "      <td>10</td>\n",
       "      <td>5</td>\n",
       "      <td>28</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>74</td>\n",
       "      <td>129</td>\n",
       "      <td>16</td>\n",
       "      <td>114</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>97</td>\n",
       "      <td>121</td>\n",
       "      <td>122</td>\n",
       "      <td>29</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>141</td>\n",
       "      <td>73</td>\n",
       "      <td>120</td>\n",
       "      <td>147</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>126</td>\n",
       "      <td>132</td>\n",
       "      <td>86</td>\n",
       "      <td>116</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>85</td>\n",
       "      <td>3</td>\n",
       "      <td>42</td>\n",
       "      <td>121</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>142</td>\n",
       "      <td>65</td>\n",
       "      <td>1</td>\n",
       "      <td>124</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>136</td>\n",
       "      <td>141</td>\n",
       "      <td>122</td>\n",
       "      <td>86</td>\n",
       "      <td>113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>15</td>\n",
       "      <td>37</td>\n",
       "      <td>124</td>\n",
       "      <td>110</td>\n",
       "      <td>102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>63</td>\n",
       "      <td>30</td>\n",
       "      <td>44</td>\n",
       "      <td>69</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>59</td>\n",
       "      <td>38</td>\n",
       "      <td>113</td>\n",
       "      <td>109</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>5</td>\n",
       "      <td>51</td>\n",
       "      <td>87</td>\n",
       "      <td>58</td>\n",
       "      <td>126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>53</td>\n",
       "      <td>97</td>\n",
       "      <td>76</td>\n",
       "      <td>37</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>42</td>\n",
       "      <td>148</td>\n",
       "      <td>107</td>\n",
       "      <td>97</td>\n",
       "      <td>143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>70</td>\n",
       "      <td>138</td>\n",
       "      <td>69</td>\n",
       "      <td>68</td>\n",
       "      <td>134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>47</td>\n",
       "      <td>136</td>\n",
       "      <td>113</td>\n",
       "      <td>22</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>31</td>\n",
       "      <td>137</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>148</td>\n",
       "      <td>74</td>\n",
       "      <td>134</td>\n",
       "      <td>4</td>\n",
       "      <td>124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>102</td>\n",
       "      <td>81</td>\n",
       "      <td>138</td>\n",
       "      <td>128</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>27</td>\n",
       "      <td>111</td>\n",
       "      <td>13</td>\n",
       "      <td>70</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>28</td>\n",
       "      <td>93</td>\n",
       "      <td>121</td>\n",
       "      <td>68</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>136</td>\n",
       "      <td>43</td>\n",
       "      <td>25</td>\n",
       "      <td>97</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>111</td>\n",
       "      <td>70</td>\n",
       "      <td>12</td>\n",
       "      <td>38</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>96</td>\n",
       "      <td>103</td>\n",
       "      <td>147</td>\n",
       "      <td>86</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>46</td>\n",
       "      <td>63</td>\n",
       "      <td>149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>7</td>\n",
       "      <td>75</td>\n",
       "      <td>97</td>\n",
       "      <td>108</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>88</td>\n",
       "      <td>6</td>\n",
       "      <td>145</td>\n",
       "      <td>116</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>33</td>\n",
       "      <td>74</td>\n",
       "      <td>106</td>\n",
       "      <td>50</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>74</td>\n",
       "      <td>28</td>\n",
       "      <td>26</td>\n",
       "      <td>100</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>76</td>\n",
       "      <td>18</td>\n",
       "      <td>101</td>\n",
       "      <td>126</td>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>144</td>\n",
       "      <td>124</td>\n",
       "      <td>77</td>\n",
       "      <td>92</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>36</td>\n",
       "      <td>98</td>\n",
       "      <td>48</td>\n",
       "      <td>43</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>51</td>\n",
       "      <td>143</td>\n",
       "      <td>68</td>\n",
       "      <td>34</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>149</td>\n",
       "      <td>117</td>\n",
       "      <td>18</td>\n",
       "      <td>141</td>\n",
       "      <td>120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>8</td>\n",
       "      <td>139</td>\n",
       "      <td>146</td>\n",
       "      <td>112</td>\n",
       "      <td>122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>115</td>\n",
       "      <td>101</td>\n",
       "      <td>64</td>\n",
       "      <td>62</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>140</td>\n",
       "      <td>45</td>\n",
       "      <td>148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>65</td>\n",
       "      <td>43</td>\n",
       "      <td>68</td>\n",
       "      <td>109</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>31</td>\n",
       "      <td>100</td>\n",
       "      <td>110</td>\n",
       "      <td>49</td>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>29</td>\n",
       "      <td>46</td>\n",
       "      <td>69</td>\n",
       "      <td>57</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>146</td>\n",
       "      <td>86</td>\n",
       "      <td>18</td>\n",
       "      <td>22</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>71</td>\n",
       "      <td>50</td>\n",
       "      <td>40</td>\n",
       "      <td>90</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>4</td>\n",
       "      <td>100</td>\n",
       "      <td>147</td>\n",
       "      <td>116</td>\n",
       "      <td>110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>55</td>\n",
       "      <td>87</td>\n",
       "      <td>93</td>\n",
       "      <td>78</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>5</td>\n",
       "      <td>109</td>\n",
       "      <td>124</td>\n",
       "      <td>87</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>10</td>\n",
       "      <td>118</td>\n",
       "      <td>139</td>\n",
       "      <td>50</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>32</td>\n",
       "      <td>12</td>\n",
       "      <td>71</td>\n",
       "      <td>36</td>\n",
       "      <td>124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>94</td>\n",
       "      <td>16</td>\n",
       "      <td>138</td>\n",
       "      <td>13</td>\n",
       "      <td>149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>65</td>\n",
       "      <td>101</td>\n",
       "      <td>123</td>\n",
       "      <td>128</td>\n",
       "      <td>86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>43</td>\n",
       "      <td>94</td>\n",
       "      <td>10</td>\n",
       "      <td>29</td>\n",
       "      <td>132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>68</td>\n",
       "      <td>135</td>\n",
       "      <td>94</td>\n",
       "      <td>28</td>\n",
       "      <td>125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>30</td>\n",
       "      <td>60</td>\n",
       "      <td>98</td>\n",
       "      <td>27</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>89</td>\n",
       "      <td>16</td>\n",
       "      <td>10</td>\n",
       "      <td>135</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>104</td>\n",
       "      <td>139</td>\n",
       "      <td>97</td>\n",
       "      <td>29</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>5</td>\n",
       "      <td>29</td>\n",
       "      <td>41</td>\n",
       "      <td>99</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>19</td>\n",
       "      <td>102</td>\n",
       "      <td>135</td>\n",
       "      <td>41</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>58</td>\n",
       "      <td>100</td>\n",
       "      <td>70</td>\n",
       "      <td>82</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>84</td>\n",
       "      <td>97</td>\n",
       "      <td>129</td>\n",
       "      <td>76</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>131</td>\n",
       "      <td>15</td>\n",
       "      <td>7</td>\n",
       "      <td>44</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>79</td>\n",
       "      <td>37</td>\n",
       "      <td>95</td>\n",
       "      <td>128</td>\n",
       "      <td>116</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Python   En  Math  Physic  Chem\n",
       "100     122   10     5      28    57\n",
       "101      74  129    16     114    26\n",
       "102      97  121   122      29    65\n",
       "103     141   73   120     147     1\n",
       "104     126  132    86     116    17\n",
       "105      85    3    42     121    66\n",
       "106     142   65     1     124    83\n",
       "107     136  141   122      86   113\n",
       "108      15   37   124     110   102\n",
       "109      63   30    44      69    58\n",
       "110      59   38   113     109    16\n",
       "111       5   51    87      58   126\n",
       "112      53   97    76      37    45\n",
       "113      42  148   107      97   143\n",
       "114      70  138    69      68   134\n",
       "115      47  136   113      22    94\n",
       "116      31  137     6      20    28\n",
       "117     148   74   134       4   124\n",
       "118     102   81   138     128    32\n",
       "119      27  111    13      70    22\n",
       "120      28   93   121      68     4\n",
       "121     136   43    25      97    19\n",
       "122     111   70    12      38    58\n",
       "123      96  103   147      86     8\n",
       "124      10   10    46      63   149\n",
       "125       7   75    97     108    31\n",
       "126      88    6   145     116    55\n",
       "127      33   74   106      50    46\n",
       "128      74   28    26     100    76\n",
       "129      76   18   101     126   133\n",
       "..      ...  ...   ...     ...   ...\n",
       "170     144  124    77      92    82\n",
       "171      36   98    48      43    80\n",
       "172      51  143    68      34    74\n",
       "173     149  117    18     141   120\n",
       "174       8  139   146     112   122\n",
       "175     115  101    64      62     9\n",
       "176      10    7   140      45   148\n",
       "177      65   43    68     109    18\n",
       "178      31  100   110      49   123\n",
       "179      29   46    69      57    90\n",
       "180     146   86    18      22    46\n",
       "181      71   50    40      90   140\n",
       "182       4  100   147     116   110\n",
       "183      55   87    93      78    34\n",
       "184       5  109   124      87    82\n",
       "185      10  118   139      50    51\n",
       "186      32   12    71      36   124\n",
       "187      94   16   138      13   149\n",
       "188      65  101   123     128    86\n",
       "189      43   94    10      29   132\n",
       "190      68  135    94      28   125\n",
       "191      30   60    98      27    15\n",
       "192      89   16    10     135     4\n",
       "193     104  139    97      29    17\n",
       "194       5   29    41      99    91\n",
       "195      19  102   135      41    40\n",
       "196      58  100    70      82    64\n",
       "197      84   97   129      76    13\n",
       "198     131   15     7      44   114\n",
       "199      79   37    95     128   116\n",
       "\n",
       "[100 rows x 5 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = DataFrame(np.random.randint(0,150,size = (100,5)),index = np.arange(100,200),columns=['Python','En','Math','Physic','Chem'])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Python    False\n",
       "En        False\n",
       "Math      False\n",
       "Physic    False\n",
       "Chem      False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 判断DataFrame是否存在空数据\n",
    "df.isnull().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Python    True\n",
       "En        True\n",
       "Math      True\n",
       "Physic    True\n",
       "Chem      True\n",
       "dtype: bool"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.notnull().all()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "500"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "100*5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(50):\n",
    "    # 行索引\n",
    "    index = np.random.randint(100,200,size =1)[0]\n",
    "\n",
    "    cols = df.columns\n",
    "\n",
    "    # 列索引\n",
    "    col = np.random.choice(cols)\n",
    "\n",
    "    df.loc[index,col] = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(20):\n",
    "    # 行索引\n",
    "    index = np.random.randint(100,200,size =1)[0]\n",
    "\n",
    "    cols = df.columns\n",
    "\n",
    "    # 列索引\n",
    "    col = np.random.choice(cols)\n",
    "\n",
    "#     not a number 不是一个数\n",
    "    df.loc[index,col] = np.NAN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Python</th>\n",
       "      <th>En</th>\n",
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       "      <th>Physic</th>\n",
       "      <th>Chem</th>\n",
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       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>122.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>57.0</td>\n",
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       "      <th>101</th>\n",
       "      <td>NaN</td>\n",
       "      <td>129.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>26.0</td>\n",
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       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>97.0</td>\n",
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       "      <th>103</th>\n",
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       "      <td>120.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>1.0</td>\n",
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       "      <th>104</th>\n",
       "      <td>126.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>86.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>85.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>66.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>142.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>136.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>86.0</td>\n",
       "      <td>113.0</td>\n",
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       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>15.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>102.0</td>\n",
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       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>63.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>69.0</td>\n",
       "      <td>58.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>113.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>5.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>126.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>53.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>45.0</td>\n",
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       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>42.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97.0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>70.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>134.0</td>\n",
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       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>NaN</td>\n",
       "      <td>136.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>94.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>31.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>148.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>134.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>124.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>102.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>32.0</td>\n",
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       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>27.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>28.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>136.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>111.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>58.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>NaN</td>\n",
       "      <td>103.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>7.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>88.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>33.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>74.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>76.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>76.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>144.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>36.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.0</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>51.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>68.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>74.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>149.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>8.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>115.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>64.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>148.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>NaN</td>\n",
       "      <td>43.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>31.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49.0</td>\n",
       "      <td>123.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>29.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>146.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>71.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>4.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>110.0</td>\n",
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       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>55.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>NaN</td>\n",
       "      <td>109.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>10.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>51.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>32.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>94.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>138.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>65.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>86.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>43.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.0</td>\n",
       "      <td>132.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>68.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>30.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>89.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>104.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>5.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>19.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>64.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>NaN</td>\n",
       "      <td>97.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>131.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.0</td>\n",
       "      <td>114.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>79.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>95.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Python     En   Math  Physic   Chem\n",
       "100   122.0   10.0    5.0    28.0   57.0\n",
       "101     NaN  129.0   16.0   114.0   26.0\n",
       "102    97.0  121.0  122.0    29.0   65.0\n",
       "103   141.0   73.0  120.0   147.0    1.0\n",
       "104   126.0    NaN   86.0   116.0   17.0\n",
       "105    85.0    NaN   42.0   121.0   66.0\n",
       "106   142.0   65.0    1.0   124.0   83.0\n",
       "107   136.0  141.0    NaN    86.0  113.0\n",
       "108    15.0   37.0  124.0   110.0  102.0\n",
       "109    63.0   30.0    NaN    69.0   58.0\n",
       "110     NaN    NaN  113.0   109.0   16.0\n",
       "111     5.0   51.0   87.0    58.0  126.0\n",
       "112    53.0   97.0   76.0    37.0   45.0\n",
       "113    42.0  148.0    NaN    97.0    NaN\n",
       "114    70.0  138.0   69.0    68.0  134.0\n",
       "115     NaN  136.0  113.0    22.0   94.0\n",
       "116    31.0  137.0    6.0    20.0   28.0\n",
       "117   148.0   74.0  134.0     4.0  124.0\n",
       "118   102.0   81.0  138.0   128.0   32.0\n",
       "119    27.0  111.0   13.0     NaN   22.0\n",
       "120    28.0   93.0  121.0     NaN    4.0\n",
       "121   136.0    NaN   25.0    97.0   19.0\n",
       "122   111.0   70.0   12.0    38.0   58.0\n",
       "123     NaN  103.0  147.0    86.0    8.0\n",
       "124    10.0   10.0   46.0    63.0  149.0\n",
       "125     7.0   75.0   97.0   108.0   31.0\n",
       "126    88.0    6.0    NaN     NaN   55.0\n",
       "127    33.0   74.0  106.0    50.0   46.0\n",
       "128    74.0   28.0   26.0   100.0   76.0\n",
       "129    76.0   18.0  101.0     NaN    NaN\n",
       "..      ...    ...    ...     ...    ...\n",
       "170   144.0  124.0   77.0    92.0   82.0\n",
       "171    36.0   98.0    NaN    43.0   80.0\n",
       "172    51.0    NaN   68.0    34.0   74.0\n",
       "173   149.0    NaN   18.0   141.0    NaN\n",
       "174     8.0  139.0  146.0   112.0    NaN\n",
       "175   115.0    NaN   64.0    62.0    9.0\n",
       "176     NaN    7.0  140.0    45.0  148.0\n",
       "177     NaN   43.0   68.0   109.0   18.0\n",
       "178    31.0  100.0    NaN    49.0  123.0\n",
       "179    29.0   46.0   69.0    57.0   90.0\n",
       "180   146.0   86.0   18.0    22.0   46.0\n",
       "181    71.0   50.0   40.0     NaN  140.0\n",
       "182     4.0  100.0  147.0   116.0  110.0\n",
       "183    55.0   87.0   93.0     NaN   34.0\n",
       "184     NaN  109.0  124.0    87.0   82.0\n",
       "185    10.0  118.0  139.0    50.0   51.0\n",
       "186    32.0   12.0   71.0    36.0    NaN\n",
       "187    94.0    NaN  138.0    13.0  149.0\n",
       "188    65.0  101.0  123.0   128.0   86.0\n",
       "189    43.0   94.0    NaN    29.0  132.0\n",
       "190    68.0  135.0   94.0    28.0  125.0\n",
       "191    30.0   60.0   98.0     NaN   15.0\n",
       "192    89.0   16.0   10.0   135.0    4.0\n",
       "193   104.0  139.0   97.0    29.0   17.0\n",
       "194     5.0   29.0   41.0    99.0    NaN\n",
       "195    19.0  102.0  135.0    41.0   40.0\n",
       "196    58.0    NaN   70.0    82.0   64.0\n",
       "197     NaN   97.0  129.0    76.0   13.0\n",
       "198   131.0   15.0    NaN    44.0  114.0\n",
       "199    79.0    NaN   95.0   128.0    NaN\n",
       "\n",
       "[100 rows x 5 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Python    True\n",
       "En        True\n",
       "Math      True\n",
       "Physic    True\n",
       "Chem      True\n",
       "dtype: bool"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Python    14\n",
       "En        14\n",
       "Math      15\n",
       "Physic    11\n",
       "Chem      13\n",
       "dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = df.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Python    14\n",
       "En        14\n",
       "Math      15\n",
       "Physic    11\n",
       "Chem      13\n",
       "dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Python</th>\n",
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       "      <td>5.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>57.0</td>\n",
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       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>100.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>26.0</td>\n",
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       "      <th>102</th>\n",
       "      <td>97.0</td>\n",
       "      <td>121.0</td>\n",
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       "      <td>29.0</td>\n",
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       "      <th>103</th>\n",
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       "      <td>73.0</td>\n",
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       "      <td>147.0</td>\n",
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       "      <th>104</th>\n",
       "      <td>126.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>17.0</td>\n",
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       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>85.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>66.0</td>\n",
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       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>142.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>83.0</td>\n",
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       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>136.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>86.0</td>\n",
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       "      <th>108</th>\n",
       "      <td>15.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>102.0</td>\n",
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       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>63.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>58.0</td>\n",
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       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>16.0</td>\n",
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       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>5.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>126.0</td>\n",
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       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>53.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>45.0</td>\n",
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       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>42.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>100.0</td>\n",
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       "      <th>114</th>\n",
       "      <td>70.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>134.0</td>\n",
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       "      <th>115</th>\n",
       "      <td>100.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>94.0</td>\n",
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       "      <th>116</th>\n",
       "      <td>31.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>28.0</td>\n",
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       "      <th>117</th>\n",
       "      <td>148.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>134.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>124.0</td>\n",
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       "      <th>118</th>\n",
       "      <td>102.0</td>\n",
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       "      <th>120</th>\n",
       "      <td>28.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <th>121</th>\n",
       "      <td>136.0</td>\n",
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       "      <td>25.0</td>\n",
       "      <td>97.0</td>\n",
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       "      <th>122</th>\n",
       "      <td>111.0</td>\n",
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       "      <td>12.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>58.0</td>\n",
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       "      <th>123</th>\n",
       "      <td>100.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>8.0</td>\n",
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       "      <th>124</th>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>149.0</td>\n",
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       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>7.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>31.0</td>\n",
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       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>88.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>55.0</td>\n",
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       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>33.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>46.0</td>\n",
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       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>74.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>76.0</td>\n",
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       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>76.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>144.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>82.0</td>\n",
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       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>36.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>80.0</td>\n",
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       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>51.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>74.0</td>\n",
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       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>149.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>100.0</td>\n",
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       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>8.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>100.0</td>\n",
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       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>115.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>9.0</td>\n",
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       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>100.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>148.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>100.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>18.0</td>\n",
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       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>31.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>123.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>29.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>146.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>71.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>140.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>4.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>55.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>100.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>10.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>51.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>32.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>94.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>65.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>86.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>43.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>132.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>68.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>30.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>89.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>104.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>5.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>19.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>58.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>64.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>100.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>131.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>114.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>79.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Python     En   Math  Physic   Chem\n",
       "100   122.0   10.0    5.0    28.0   57.0\n",
       "101   100.0  129.0   16.0   114.0   26.0\n",
       "102    97.0  121.0  122.0    29.0   65.0\n",
       "103   141.0   73.0  120.0   147.0    1.0\n",
       "104   126.0  100.0   86.0   116.0   17.0\n",
       "105    85.0  100.0   42.0   121.0   66.0\n",
       "106   142.0   65.0    1.0   124.0   83.0\n",
       "107   136.0  141.0  100.0    86.0  113.0\n",
       "108    15.0   37.0  124.0   110.0  102.0\n",
       "109    63.0   30.0  100.0    69.0   58.0\n",
       "110   100.0  100.0  113.0   109.0   16.0\n",
       "111     5.0   51.0   87.0    58.0  126.0\n",
       "112    53.0   97.0   76.0    37.0   45.0\n",
       "113    42.0  148.0  100.0    97.0  100.0\n",
       "114    70.0  138.0   69.0    68.0  134.0\n",
       "115   100.0  136.0  113.0    22.0   94.0\n",
       "116    31.0  137.0    6.0    20.0   28.0\n",
       "117   148.0   74.0  134.0     4.0  124.0\n",
       "118   102.0   81.0  138.0   128.0   32.0\n",
       "119    27.0  111.0   13.0   100.0   22.0\n",
       "120    28.0   93.0  121.0   100.0    4.0\n",
       "121   136.0  100.0   25.0    97.0   19.0\n",
       "122   111.0   70.0   12.0    38.0   58.0\n",
       "123   100.0  103.0  147.0    86.0    8.0\n",
       "124    10.0   10.0   46.0    63.0  149.0\n",
       "125     7.0   75.0   97.0   108.0   31.0\n",
       "126    88.0    6.0  100.0   100.0   55.0\n",
       "127    33.0   74.0  106.0    50.0   46.0\n",
       "128    74.0   28.0   26.0   100.0   76.0\n",
       "129    76.0   18.0  101.0   100.0  100.0\n",
       "..      ...    ...    ...     ...    ...\n",
       "170   144.0  124.0   77.0    92.0   82.0\n",
       "171    36.0   98.0  100.0    43.0   80.0\n",
       "172    51.0  100.0   68.0    34.0   74.0\n",
       "173   149.0  100.0   18.0   141.0  100.0\n",
       "174     8.0  139.0  146.0   112.0  100.0\n",
       "175   115.0  100.0   64.0    62.0    9.0\n",
       "176   100.0    7.0  140.0    45.0  148.0\n",
       "177   100.0   43.0   68.0   109.0   18.0\n",
       "178    31.0  100.0  100.0    49.0  123.0\n",
       "179    29.0   46.0   69.0    57.0   90.0\n",
       "180   146.0   86.0   18.0    22.0   46.0\n",
       "181    71.0   50.0   40.0   100.0  140.0\n",
       "182     4.0  100.0  147.0   116.0  110.0\n",
       "183    55.0   87.0   93.0   100.0   34.0\n",
       "184   100.0  109.0  124.0    87.0   82.0\n",
       "185    10.0  118.0  139.0    50.0   51.0\n",
       "186    32.0   12.0   71.0    36.0  100.0\n",
       "187    94.0  100.0  138.0    13.0  149.0\n",
       "188    65.0  101.0  123.0   128.0   86.0\n",
       "189    43.0   94.0  100.0    29.0  132.0\n",
       "190    68.0  135.0   94.0    28.0  125.0\n",
       "191    30.0   60.0   98.0   100.0   15.0\n",
       "192    89.0   16.0   10.0   135.0    4.0\n",
       "193   104.0  139.0   97.0    29.0   17.0\n",
       "194     5.0   29.0   41.0    99.0  100.0\n",
       "195    19.0  102.0  135.0    41.0   40.0\n",
       "196    58.0  100.0   70.0    82.0   64.0\n",
       "197   100.0   97.0  129.0    76.0   13.0\n",
       "198   131.0   15.0  100.0    44.0  114.0\n",
       "199    79.0  100.0   95.0   128.0  100.0\n",
       "\n",
       "[100 rows x 5 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 固定值填充\n",
    "df2.fillna(value=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Python    71.662791\n",
       "En        75.627907\n",
       "Math      77.929412\n",
       "Physic    73.471910\n",
       "Chem      69.080460\n",
       "dtype: float64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "      <th>Python</th>\n",
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       "      <th>100</th>\n",
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       "      <td>26</td>\n",
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       "      <th>102</th>\n",
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       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>126</td>\n",
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       "      <td>116</td>\n",
       "      <td>17</td>\n",
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       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>85</td>\n",
       "      <td>75</td>\n",
       "      <td>42</td>\n",
       "      <td>121</td>\n",
       "      <td>66</td>\n",
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       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>142</td>\n",
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       "      <td>1</td>\n",
       "      <td>124</td>\n",
       "      <td>83</td>\n",
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       "      <th>107</th>\n",
       "      <td>136</td>\n",
       "      <td>141</td>\n",
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       "      <td>86</td>\n",
       "      <td>113</td>\n",
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       "      <th>108</th>\n",
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       "      <td>102</td>\n",
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       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>63</td>\n",
       "      <td>30</td>\n",
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       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>71</td>\n",
       "      <td>75</td>\n",
       "      <td>113</td>\n",
       "      <td>109</td>\n",
       "      <td>16</td>\n",
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       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>5</td>\n",
       "      <td>51</td>\n",
       "      <td>87</td>\n",
       "      <td>58</td>\n",
       "      <td>126</td>\n",
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       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>53</td>\n",
       "      <td>97</td>\n",
       "      <td>76</td>\n",
       "      <td>37</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>42</td>\n",
       "      <td>148</td>\n",
       "      <td>77</td>\n",
       "      <td>97</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>70</td>\n",
       "      <td>138</td>\n",
       "      <td>69</td>\n",
       "      <td>68</td>\n",
       "      <td>134</td>\n",
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       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>71</td>\n",
       "      <td>136</td>\n",
       "      <td>113</td>\n",
       "      <td>22</td>\n",
       "      <td>94</td>\n",
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       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>31</td>\n",
       "      <td>137</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>148</td>\n",
       "      <td>74</td>\n",
       "      <td>134</td>\n",
       "      <td>4</td>\n",
       "      <td>124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>102</td>\n",
       "      <td>81</td>\n",
       "      <td>138</td>\n",
       "      <td>128</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>27</td>\n",
       "      <td>111</td>\n",
       "      <td>13</td>\n",
       "      <td>73</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>28</td>\n",
       "      <td>93</td>\n",
       "      <td>121</td>\n",
       "      <td>73</td>\n",
       "      <td>4</td>\n",
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       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>136</td>\n",
       "      <td>75</td>\n",
       "      <td>25</td>\n",
       "      <td>97</td>\n",
       "      <td>19</td>\n",
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       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>111</td>\n",
       "      <td>70</td>\n",
       "      <td>12</td>\n",
       "      <td>38</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>71</td>\n",
       "      <td>103</td>\n",
       "      <td>147</td>\n",
       "      <td>86</td>\n",
       "      <td>8</td>\n",
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       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>46</td>\n",
       "      <td>63</td>\n",
       "      <td>149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>7</td>\n",
       "      <td>75</td>\n",
       "      <td>97</td>\n",
       "      <td>108</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>88</td>\n",
       "      <td>6</td>\n",
       "      <td>77</td>\n",
       "      <td>73</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>33</td>\n",
       "      <td>74</td>\n",
       "      <td>106</td>\n",
       "      <td>50</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>74</td>\n",
       "      <td>28</td>\n",
       "      <td>26</td>\n",
       "      <td>100</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>76</td>\n",
       "      <td>18</td>\n",
       "      <td>101</td>\n",
       "      <td>73</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>144</td>\n",
       "      <td>124</td>\n",
       "      <td>77</td>\n",
       "      <td>92</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>36</td>\n",
       "      <td>98</td>\n",
       "      <td>77</td>\n",
       "      <td>43</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>51</td>\n",
       "      <td>75</td>\n",
       "      <td>68</td>\n",
       "      <td>34</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>149</td>\n",
       "      <td>75</td>\n",
       "      <td>18</td>\n",
       "      <td>141</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>8</td>\n",
       "      <td>139</td>\n",
       "      <td>146</td>\n",
       "      <td>112</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>115</td>\n",
       "      <td>75</td>\n",
       "      <td>64</td>\n",
       "      <td>62</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>71</td>\n",
       "      <td>7</td>\n",
       "      <td>140</td>\n",
       "      <td>45</td>\n",
       "      <td>148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>71</td>\n",
       "      <td>43</td>\n",
       "      <td>68</td>\n",
       "      <td>109</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>31</td>\n",
       "      <td>100</td>\n",
       "      <td>77</td>\n",
       "      <td>49</td>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>29</td>\n",
       "      <td>46</td>\n",
       "      <td>69</td>\n",
       "      <td>57</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>146</td>\n",
       "      <td>86</td>\n",
       "      <td>18</td>\n",
       "      <td>22</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>71</td>\n",
       "      <td>50</td>\n",
       "      <td>40</td>\n",
       "      <td>73</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>4</td>\n",
       "      <td>100</td>\n",
       "      <td>147</td>\n",
       "      <td>116</td>\n",
       "      <td>110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>55</td>\n",
       "      <td>87</td>\n",
       "      <td>93</td>\n",
       "      <td>73</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>71</td>\n",
       "      <td>109</td>\n",
       "      <td>124</td>\n",
       "      <td>87</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>10</td>\n",
       "      <td>118</td>\n",
       "      <td>139</td>\n",
       "      <td>50</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>32</td>\n",
       "      <td>12</td>\n",
       "      <td>71</td>\n",
       "      <td>36</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>94</td>\n",
       "      <td>75</td>\n",
       "      <td>138</td>\n",
       "      <td>13</td>\n",
       "      <td>149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>65</td>\n",
       "      <td>101</td>\n",
       "      <td>123</td>\n",
       "      <td>128</td>\n",
       "      <td>86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>43</td>\n",
       "      <td>94</td>\n",
       "      <td>77</td>\n",
       "      <td>29</td>\n",
       "      <td>132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>68</td>\n",
       "      <td>135</td>\n",
       "      <td>94</td>\n",
       "      <td>28</td>\n",
       "      <td>125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>30</td>\n",
       "      <td>60</td>\n",
       "      <td>98</td>\n",
       "      <td>73</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>89</td>\n",
       "      <td>16</td>\n",
       "      <td>10</td>\n",
       "      <td>135</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>104</td>\n",
       "      <td>139</td>\n",
       "      <td>97</td>\n",
       "      <td>29</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>5</td>\n",
       "      <td>29</td>\n",
       "      <td>41</td>\n",
       "      <td>99</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>19</td>\n",
       "      <td>102</td>\n",
       "      <td>135</td>\n",
       "      <td>41</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>58</td>\n",
       "      <td>75</td>\n",
       "      <td>70</td>\n",
       "      <td>82</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>71</td>\n",
       "      <td>97</td>\n",
       "      <td>129</td>\n",
       "      <td>76</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>131</td>\n",
       "      <td>15</td>\n",
       "      <td>77</td>\n",
       "      <td>44</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>79</td>\n",
       "      <td>75</td>\n",
       "      <td>95</td>\n",
       "      <td>128</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Python   En  Math  Physic  Chem\n",
       "100     122   10     5      28    57\n",
       "101      71  129    16     114    26\n",
       "102      97  121   122      29    65\n",
       "103     141   73   120     147     1\n",
       "104     126   75    86     116    17\n",
       "105      85   75    42     121    66\n",
       "106     142   65     1     124    83\n",
       "107     136  141    77      86   113\n",
       "108      15   37   124     110   102\n",
       "109      63   30    77      69    58\n",
       "110      71   75   113     109    16\n",
       "111       5   51    87      58   126\n",
       "112      53   97    76      37    45\n",
       "113      42  148    77      97    69\n",
       "114      70  138    69      68   134\n",
       "115      71  136   113      22    94\n",
       "116      31  137     6      20    28\n",
       "117     148   74   134       4   124\n",
       "118     102   81   138     128    32\n",
       "119      27  111    13      73    22\n",
       "120      28   93   121      73     4\n",
       "121     136   75    25      97    19\n",
       "122     111   70    12      38    58\n",
       "123      71  103   147      86     8\n",
       "124      10   10    46      63   149\n",
       "125       7   75    97     108    31\n",
       "126      88    6    77      73    55\n",
       "127      33   74   106      50    46\n",
       "128      74   28    26     100    76\n",
       "129      76   18   101      73    69\n",
       "..      ...  ...   ...     ...   ...\n",
       "170     144  124    77      92    82\n",
       "171      36   98    77      43    80\n",
       "172      51   75    68      34    74\n",
       "173     149   75    18     141    69\n",
       "174       8  139   146     112    69\n",
       "175     115   75    64      62     9\n",
       "176      71    7   140      45   148\n",
       "177      71   43    68     109    18\n",
       "178      31  100    77      49   123\n",
       "179      29   46    69      57    90\n",
       "180     146   86    18      22    46\n",
       "181      71   50    40      73   140\n",
       "182       4  100   147     116   110\n",
       "183      55   87    93      73    34\n",
       "184      71  109   124      87    82\n",
       "185      10  118   139      50    51\n",
       "186      32   12    71      36    69\n",
       "187      94   75   138      13   149\n",
       "188      65  101   123     128    86\n",
       "189      43   94    77      29   132\n",
       "190      68  135    94      28   125\n",
       "191      30   60    98      73    15\n",
       "192      89   16    10     135     4\n",
       "193     104  139    97      29    17\n",
       "194       5   29    41      99    69\n",
       "195      19  102   135      41    40\n",
       "196      58   75    70      82    64\n",
       "197      71   97   129      76    13\n",
       "198     131   15    77      44   114\n",
       "199      79   75    95     128    69\n",
       "\n",
       "[100 rows x 5 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 均值\n",
    "df3 = df2.fillna(value=df2.mean())\n",
    "df3.astype(np.int16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 6, 18,  1, 17, 19,  5, 17, 16, 13,  3])"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nd = np.random.randint(0,20,size = 10)\n",
    "nd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1,  3,  5,  6, 13, 16, 17, 17, 18, 19])"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nd.sort()\n",
    "nd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14.5"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(13 + 16)/2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14.5"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.median(nd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Python</th>\n",
       "      <th>En</th>\n",
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       "      <th>Physic</th>\n",
       "      <th>Chem</th>\n",
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       "      <th>100</th>\n",
       "      <td>122.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>57.0</td>\n",
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       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>68.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>26.0</td>\n",
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       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>97.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>29.0</td>\n",
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       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>141.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>126.0</td>\n",
       "      <td>82.5</td>\n",
       "      <td>86.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>85.0</td>\n",
       "      <td>82.5</td>\n",
       "      <td>42.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>66.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>142.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>136.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>113.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>15.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>102.0</td>\n",
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       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>63.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>58.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>68.0</td>\n",
       "      <td>82.5</td>\n",
       "      <td>113.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>5.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>126.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>53.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>42.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>65.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>70.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>134.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>68.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>94.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>31.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>148.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>134.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>124.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>102.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>27.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>28.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>136.0</td>\n",
       "      <td>82.5</td>\n",
       "      <td>25.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>111.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>58.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>68.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>7.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>88.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>33.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>74.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>76.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>76.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>65.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>144.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>36.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>51.0</td>\n",
       "      <td>82.5</td>\n",
       "      <td>68.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>74.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>149.0</td>\n",
       "      <td>82.5</td>\n",
       "      <td>18.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>65.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>8.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>65.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>115.0</td>\n",
       "      <td>82.5</td>\n",
       "      <td>64.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>68.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>148.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>68.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>31.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>123.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>29.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>146.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>71.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>140.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>4.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>55.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>68.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>10.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>51.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>32.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>65.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>94.0</td>\n",
       "      <td>82.5</td>\n",
       "      <td>138.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>65.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>86.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>43.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>132.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>68.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>30.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>89.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>104.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>5.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>65.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>19.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>58.0</td>\n",
       "      <td>82.5</td>\n",
       "      <td>70.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>64.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>68.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>131.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>114.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>79.0</td>\n",
       "      <td>82.5</td>\n",
       "      <td>95.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>65.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Python     En   Math  Physic   Chem\n",
       "100   122.0   10.0    5.0    28.0   57.0\n",
       "101    68.0  129.0   16.0   114.0   26.0\n",
       "102    97.0  121.0  122.0    29.0   65.0\n",
       "103   141.0   73.0  120.0   147.0    1.0\n",
       "104   126.0   82.5   86.0   116.0   17.0\n",
       "105    85.0   82.5   42.0   121.0   66.0\n",
       "106   142.0   65.0    1.0   124.0   83.0\n",
       "107   136.0  141.0   86.0    86.0  113.0\n",
       "108    15.0   37.0  124.0   110.0  102.0\n",
       "109    63.0   30.0   86.0    69.0   58.0\n",
       "110    68.0   82.5  113.0   109.0   16.0\n",
       "111     5.0   51.0   87.0    58.0  126.0\n",
       "112    53.0   97.0   76.0    37.0   45.0\n",
       "113    42.0  148.0   86.0    97.0   65.0\n",
       "114    70.0  138.0   69.0    68.0  134.0\n",
       "115    68.0  136.0  113.0    22.0   94.0\n",
       "116    31.0  137.0    6.0    20.0   28.0\n",
       "117   148.0   74.0  134.0     4.0  124.0\n",
       "118   102.0   81.0  138.0   128.0   32.0\n",
       "119    27.0  111.0   13.0    69.0   22.0\n",
       "120    28.0   93.0  121.0    69.0    4.0\n",
       "121   136.0   82.5   25.0    97.0   19.0\n",
       "122   111.0   70.0   12.0    38.0   58.0\n",
       "123    68.0  103.0  147.0    86.0    8.0\n",
       "124    10.0   10.0   46.0    63.0  149.0\n",
       "125     7.0   75.0   97.0   108.0   31.0\n",
       "126    88.0    6.0   86.0    69.0   55.0\n",
       "127    33.0   74.0  106.0    50.0   46.0\n",
       "128    74.0   28.0   26.0   100.0   76.0\n",
       "129    76.0   18.0  101.0    69.0   65.0\n",
       "..      ...    ...    ...     ...    ...\n",
       "170   144.0  124.0   77.0    92.0   82.0\n",
       "171    36.0   98.0   86.0    43.0   80.0\n",
       "172    51.0   82.5   68.0    34.0   74.0\n",
       "173   149.0   82.5   18.0   141.0   65.0\n",
       "174     8.0  139.0  146.0   112.0   65.0\n",
       "175   115.0   82.5   64.0    62.0    9.0\n",
       "176    68.0    7.0  140.0    45.0  148.0\n",
       "177    68.0   43.0   68.0   109.0   18.0\n",
       "178    31.0  100.0   86.0    49.0  123.0\n",
       "179    29.0   46.0   69.0    57.0   90.0\n",
       "180   146.0   86.0   18.0    22.0   46.0\n",
       "181    71.0   50.0   40.0    69.0  140.0\n",
       "182     4.0  100.0  147.0   116.0  110.0\n",
       "183    55.0   87.0   93.0    69.0   34.0\n",
       "184    68.0  109.0  124.0    87.0   82.0\n",
       "185    10.0  118.0  139.0    50.0   51.0\n",
       "186    32.0   12.0   71.0    36.0   65.0\n",
       "187    94.0   82.5  138.0    13.0  149.0\n",
       "188    65.0  101.0  123.0   128.0   86.0\n",
       "189    43.0   94.0   86.0    29.0  132.0\n",
       "190    68.0  135.0   94.0    28.0  125.0\n",
       "191    30.0   60.0   98.0    69.0   15.0\n",
       "192    89.0   16.0   10.0   135.0    4.0\n",
       "193   104.0  139.0   97.0    29.0   17.0\n",
       "194     5.0   29.0   41.0    99.0   65.0\n",
       "195    19.0  102.0  135.0    41.0   40.0\n",
       "196    58.0   82.5   70.0    82.0   64.0\n",
       "197    68.0   97.0  129.0    76.0   13.0\n",
       "198   131.0   15.0   86.0    44.0  114.0\n",
       "199    79.0   82.5   95.0   128.0   65.0\n",
       "\n",
       "[100 rows x 5 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 中位数填充\n",
    "df2.median()\n",
    "df4 = df2.fillna(df2.median())\n",
    "df4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Python</th>\n",
       "      <th>En</th>\n",
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       "      <th>Physic</th>\n",
       "      <th>Chem</th>\n",
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       "  <tbody>\n",
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       "      <th>100</th>\n",
       "      <td>122.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>57.0</td>\n",
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       "      <th>101</th>\n",
       "      <td>NaN</td>\n",
       "      <td>129.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>26.0</td>\n",
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       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>97.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>29.0</td>\n",
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       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>141.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>126.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>86.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>85.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>66.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>142.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>136.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>86.0</td>\n",
       "      <td>113.0</td>\n",
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       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>15.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>102.0</td>\n",
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       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>63.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>69.0</td>\n",
       "      <td>58.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>113.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>5.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>126.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>53.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>45.0</td>\n",
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       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>42.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>70.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>134.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>NaN</td>\n",
       "      <td>136.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>94.0</td>\n",
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       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>31.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>148.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>134.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>124.0</td>\n",
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       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>102.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>32.0</td>\n",
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       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>27.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>13.0</td>\n",
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       "      <td>22.0</td>\n",
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       "      <th>120</th>\n",
       "      <td>28.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>136.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>111.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>58.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>NaN</td>\n",
       "      <td>103.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>7.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>88.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>33.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>74.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>76.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>76.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>144.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>36.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.0</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>51.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>68.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>74.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>149.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>8.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>115.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>64.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>148.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>NaN</td>\n",
       "      <td>43.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>31.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49.0</td>\n",
       "      <td>123.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>29.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>146.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>71.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>4.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>55.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>NaN</td>\n",
       "      <td>109.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>10.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>51.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>32.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>94.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>138.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>65.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>86.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>43.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.0</td>\n",
       "      <td>132.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>68.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>30.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>89.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>104.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>5.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>19.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>64.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>NaN</td>\n",
       "      <td>97.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>131.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.0</td>\n",
       "      <td>114.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>79.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>95.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Python     En   Math  Physic   Chem\n",
       "100   122.0   10.0    5.0    28.0   57.0\n",
       "101     NaN  129.0   16.0   114.0   26.0\n",
       "102    97.0  121.0  122.0    29.0   65.0\n",
       "103   141.0   73.0  120.0   147.0    1.0\n",
       "104   126.0    NaN   86.0   116.0   17.0\n",
       "105    85.0    NaN   42.0   121.0   66.0\n",
       "106   142.0   65.0    1.0   124.0   83.0\n",
       "107   136.0  141.0    NaN    86.0  113.0\n",
       "108    15.0   37.0  124.0   110.0  102.0\n",
       "109    63.0   30.0    NaN    69.0   58.0\n",
       "110     NaN    NaN  113.0   109.0   16.0\n",
       "111     5.0   51.0   87.0    58.0  126.0\n",
       "112    53.0   97.0   76.0    37.0   45.0\n",
       "113    42.0  148.0    NaN    97.0    NaN\n",
       "114    70.0  138.0   69.0    68.0  134.0\n",
       "115     NaN  136.0  113.0    22.0   94.0\n",
       "116    31.0  137.0    6.0    20.0   28.0\n",
       "117   148.0   74.0  134.0     4.0  124.0\n",
       "118   102.0   81.0  138.0   128.0   32.0\n",
       "119    27.0  111.0   13.0     NaN   22.0\n",
       "120    28.0   93.0  121.0     NaN    4.0\n",
       "121   136.0    NaN   25.0    97.0   19.0\n",
       "122   111.0   70.0   12.0    38.0   58.0\n",
       "123     NaN  103.0  147.0    86.0    8.0\n",
       "124    10.0   10.0   46.0    63.0  149.0\n",
       "125     7.0   75.0   97.0   108.0   31.0\n",
       "126    88.0    6.0    NaN     NaN   55.0\n",
       "127    33.0   74.0  106.0    50.0   46.0\n",
       "128    74.0   28.0   26.0   100.0   76.0\n",
       "129    76.0   18.0  101.0     NaN    NaN\n",
       "..      ...    ...    ...     ...    ...\n",
       "170   144.0  124.0   77.0    92.0   82.0\n",
       "171    36.0   98.0    NaN    43.0   80.0\n",
       "172    51.0    NaN   68.0    34.0   74.0\n",
       "173   149.0    NaN   18.0   141.0    NaN\n",
       "174     8.0  139.0  146.0   112.0    NaN\n",
       "175   115.0    NaN   64.0    62.0    9.0\n",
       "176     NaN    7.0  140.0    45.0  148.0\n",
       "177     NaN   43.0   68.0   109.0   18.0\n",
       "178    31.0  100.0    NaN    49.0  123.0\n",
       "179    29.0   46.0   69.0    57.0   90.0\n",
       "180   146.0   86.0   18.0    22.0   46.0\n",
       "181    71.0   50.0   40.0     NaN  140.0\n",
       "182     4.0  100.0  147.0   116.0  110.0\n",
       "183    55.0   87.0   93.0     NaN   34.0\n",
       "184     NaN  109.0  124.0    87.0   82.0\n",
       "185    10.0  118.0  139.0    50.0   51.0\n",
       "186    32.0   12.0   71.0    36.0    NaN\n",
       "187    94.0    NaN  138.0    13.0  149.0\n",
       "188    65.0  101.0  123.0   128.0   86.0\n",
       "189    43.0   94.0    NaN    29.0  132.0\n",
       "190    68.0  135.0   94.0    28.0  125.0\n",
       "191    30.0   60.0   98.0     NaN   15.0\n",
       "192    89.0   16.0   10.0   135.0    4.0\n",
       "193   104.0  139.0   97.0    29.0   17.0\n",
       "194     5.0   29.0   41.0    99.0    NaN\n",
       "195    19.0  102.0  135.0    41.0   40.0\n",
       "196    58.0    NaN   70.0    82.0   64.0\n",
       "197     NaN   97.0  129.0    76.0   13.0\n",
       "198   131.0   15.0    NaN    44.0  114.0\n",
       "199    79.0    NaN   95.0   128.0    NaN\n",
       "\n",
       "[100 rows x 5 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 众数填充，数量最多的那个数\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Python</th>\n",
       "      <th>En</th>\n",
       "      <th>Math</th>\n",
       "      <th>Physic</th>\n",
       "      <th>Chem</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>82</td>\n",
       "      <td>89</td>\n",
       "      <td>99</td>\n",
       "      <td>101</td>\n",
       "      <td>125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>4</td>\n",
       "      <td>31</td>\n",
       "      <td>109</td>\n",
       "      <td>32</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>56</td>\n",
       "      <td>103</td>\n",
       "      <td>56</td>\n",
       "      <td>61</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>47</td>\n",
       "      <td>100</td>\n",
       "      <td>147</td>\n",
       "      <td>138</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>38</td>\n",
       "      <td>46</td>\n",
       "      <td>82</td>\n",
       "      <td>75</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>18</td>\n",
       "      <td>11</td>\n",
       "      <td>122</td>\n",
       "      <td>3</td>\n",
       "      <td>126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>56</td>\n",
       "      <td>26</td>\n",
       "      <td>106</td>\n",
       "      <td>14</td>\n",
       "      <td>139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>3</td>\n",
       "      <td>137</td>\n",
       "      <td>75</td>\n",
       "      <td>67</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>35</td>\n",
       "      <td>47</td>\n",
       "      <td>102</td>\n",
       "      <td>60</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>86</td>\n",
       "      <td>126</td>\n",
       "      <td>57</td>\n",
       "      <td>88</td>\n",
       "      <td>149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>19</td>\n",
       "      <td>140</td>\n",
       "      <td>30</td>\n",
       "      <td>35</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>76</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>31</td>\n",
       "      <td>54</td>\n",
       "      <td>91</td>\n",
       "      <td>119</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>64</td>\n",
       "      <td>37</td>\n",
       "      <td>50</td>\n",
       "      <td>23</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>72</td>\n",
       "      <td>57</td>\n",
       "      <td>138</td>\n",
       "      <td>15</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>55</td>\n",
       "      <td>120</td>\n",
       "      <td>104</td>\n",
       "      <td>32</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>96</td>\n",
       "      <td>24</td>\n",
       "      <td>89</td>\n",
       "      <td>22</td>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>63</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>64</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>28</td>\n",
       "      <td>46</td>\n",
       "      <td>125</td>\n",
       "      <td>82</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>85</td>\n",
       "      <td>39</td>\n",
       "      <td>70</td>\n",
       "      <td>132</td>\n",
       "      <td>111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>109</td>\n",
       "      <td>90</td>\n",
       "      <td>44</td>\n",
       "      <td>74</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>2</td>\n",
       "      <td>148</td>\n",
       "      <td>103</td>\n",
       "      <td>114</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>110</td>\n",
       "      <td>29</td>\n",
       "      <td>99</td>\n",
       "      <td>80</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>109</td>\n",
       "      <td>88</td>\n",
       "      <td>81</td>\n",
       "      <td>135</td>\n",
       "      <td>71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>70</td>\n",
       "      <td>103</td>\n",
       "      <td>134</td>\n",
       "      <td>121</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>51</td>\n",
       "      <td>92</td>\n",
       "      <td>117</td>\n",
       "      <td>27</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>6</td>\n",
       "      <td>92</td>\n",
       "      <td>97</td>\n",
       "      <td>59</td>\n",
       "      <td>105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>65</td>\n",
       "      <td>90</td>\n",
       "      <td>52</td>\n",
       "      <td>148</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>4</td>\n",
       "      <td>129</td>\n",
       "      <td>17</td>\n",
       "      <td>119</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>24</td>\n",
       "      <td>100</td>\n",
       "      <td>107</td>\n",
       "      <td>28</td>\n",
       "      <td>139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2070</th>\n",
       "      <td>127</td>\n",
       "      <td>77</td>\n",
       "      <td>24</td>\n",
       "      <td>16</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2071</th>\n",
       "      <td>93</td>\n",
       "      <td>61</td>\n",
       "      <td>9</td>\n",
       "      <td>28</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2072</th>\n",
       "      <td>116</td>\n",
       "      <td>61</td>\n",
       "      <td>54</td>\n",
       "      <td>8</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2073</th>\n",
       "      <td>4</td>\n",
       "      <td>72</td>\n",
       "      <td>140</td>\n",
       "      <td>112</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2074</th>\n",
       "      <td>26</td>\n",
       "      <td>108</td>\n",
       "      <td>123</td>\n",
       "      <td>32</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2075</th>\n",
       "      <td>46</td>\n",
       "      <td>130</td>\n",
       "      <td>135</td>\n",
       "      <td>124</td>\n",
       "      <td>113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2076</th>\n",
       "      <td>33</td>\n",
       "      <td>18</td>\n",
       "      <td>136</td>\n",
       "      <td>38</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2077</th>\n",
       "      <td>107</td>\n",
       "      <td>11</td>\n",
       "      <td>129</td>\n",
       "      <td>54</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2078</th>\n",
       "      <td>84</td>\n",
       "      <td>55</td>\n",
       "      <td>129</td>\n",
       "      <td>37</td>\n",
       "      <td>87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2079</th>\n",
       "      <td>95</td>\n",
       "      <td>50</td>\n",
       "      <td>45</td>\n",
       "      <td>19</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2080</th>\n",
       "      <td>124</td>\n",
       "      <td>74</td>\n",
       "      <td>65</td>\n",
       "      <td>140</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2081</th>\n",
       "      <td>26</td>\n",
       "      <td>35</td>\n",
       "      <td>149</td>\n",
       "      <td>145</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2082</th>\n",
       "      <td>19</td>\n",
       "      <td>21</td>\n",
       "      <td>101</td>\n",
       "      <td>3</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2083</th>\n",
       "      <td>84</td>\n",
       "      <td>10</td>\n",
       "      <td>131</td>\n",
       "      <td>71</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2084</th>\n",
       "      <td>28</td>\n",
       "      <td>74</td>\n",
       "      <td>105</td>\n",
       "      <td>68</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2085</th>\n",
       "      <td>23</td>\n",
       "      <td>93</td>\n",
       "      <td>84</td>\n",
       "      <td>97</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2086</th>\n",
       "      <td>86</td>\n",
       "      <td>133</td>\n",
       "      <td>26</td>\n",
       "      <td>125</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2087</th>\n",
       "      <td>21</td>\n",
       "      <td>124</td>\n",
       "      <td>40</td>\n",
       "      <td>115</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2088</th>\n",
       "      <td>20</td>\n",
       "      <td>15</td>\n",
       "      <td>35</td>\n",
       "      <td>31</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2089</th>\n",
       "      <td>96</td>\n",
       "      <td>123</td>\n",
       "      <td>123</td>\n",
       "      <td>5</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2090</th>\n",
       "      <td>22</td>\n",
       "      <td>43</td>\n",
       "      <td>92</td>\n",
       "      <td>78</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2091</th>\n",
       "      <td>16</td>\n",
       "      <td>31</td>\n",
       "      <td>17</td>\n",
       "      <td>60</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2092</th>\n",
       "      <td>65</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2093</th>\n",
       "      <td>69</td>\n",
       "      <td>49</td>\n",
       "      <td>109</td>\n",
       "      <td>40</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2094</th>\n",
       "      <td>128</td>\n",
       "      <td>46</td>\n",
       "      <td>10</td>\n",
       "      <td>82</td>\n",
       "      <td>111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2095</th>\n",
       "      <td>26</td>\n",
       "      <td>59</td>\n",
       "      <td>8</td>\n",
       "      <td>54</td>\n",
       "      <td>149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2096</th>\n",
       "      <td>111</td>\n",
       "      <td>47</td>\n",
       "      <td>90</td>\n",
       "      <td>92</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2097</th>\n",
       "      <td>5</td>\n",
       "      <td>97</td>\n",
       "      <td>73</td>\n",
       "      <td>140</td>\n",
       "      <td>104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2098</th>\n",
       "      <td>102</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2099</th>\n",
       "      <td>97</td>\n",
       "      <td>19</td>\n",
       "      <td>77</td>\n",
       "      <td>143</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2000 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Python   En  Math  Physic  Chem\n",
       "100       82   89    99     101   125\n",
       "101        4   31   109      32     5\n",
       "102       56  103    56      61    90\n",
       "103       47  100   147     138    99\n",
       "104       38   46    82      75    44\n",
       "105       18   11   122       3   126\n",
       "106       56   26   106      14   139\n",
       "107        3  137    75      67   144\n",
       "108       35   47   102      60    63\n",
       "109       86  126    57      88   149\n",
       "110       19  140    30      35    33\n",
       "111       76    1     5      11    33\n",
       "112       31   54    91     119    69\n",
       "113       64   37    50      23    21\n",
       "114       72   57   138      15    21\n",
       "115       55  120   104      32    25\n",
       "116       96   24    89      22   146\n",
       "117       63    0     8      64    89\n",
       "118       28   46   125      82    74\n",
       "119       85   39    70     132   111\n",
       "120      109   90    44      74    39\n",
       "121        2  148   103     114    65\n",
       "122      110   29    99      80    57\n",
       "123      109   88    81     135    71\n",
       "124       70  103   134     121   121\n",
       "125       51   92   117      27    43\n",
       "126        6   92    97      59   105\n",
       "127       65   90    52     148    22\n",
       "128        4  129    17     119    13\n",
       "129       24  100   107      28   139\n",
       "...      ...  ...   ...     ...   ...\n",
       "2070     127   77    24      16    31\n",
       "2071      93   61     9      28    22\n",
       "2072     116   61    54       8    61\n",
       "2073       4   72   140     112    34\n",
       "2074      26  108   123      32    33\n",
       "2075      46  130   135     124   113\n",
       "2076      33   18   136      38    20\n",
       "2077     107   11   129      54   119\n",
       "2078      84   55   129      37    87\n",
       "2079      95   50    45      19    84\n",
       "2080     124   74    65     140    53\n",
       "2081      26   35   149     145   127\n",
       "2082      19   21   101       3    89\n",
       "2083      84   10   131      71     4\n",
       "2084      28   74   105      68    89\n",
       "2085      23   93    84      97    88\n",
       "2086      86  133    26     125    13\n",
       "2087      21  124    40     115     5\n",
       "2088      20   15    35      31    37\n",
       "2089      96  123   123       5    64\n",
       "2090      22   43    92      78    60\n",
       "2091      16   31    17      60    58\n",
       "2092      65   18    13      13    34\n",
       "2093      69   49   109      40    58\n",
       "2094     128   46    10      82   111\n",
       "2095      26   59     8      54   149\n",
       "2096     111   47    90      92    66\n",
       "2097       5   97    73     140   104\n",
       "2098     102    6     7       5   119\n",
       "2099      97   19    77     143    48\n",
       "\n",
       "[2000 rows x 5 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = DataFrame(np.random.randint(0,150,size = (2000,5)),index = np.arange(100,2100),columns=['Python','En','Math','Physic','Chem'])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(1000):\n",
    "    # 行索引\n",
    "    index = np.random.randint(100,2100,size =1)[0]\n",
    "\n",
    "    cols = df.columns\n",
    "\n",
    "    # 列索引\n",
    "    col = np.random.choice(cols)\n",
    "\n",
    "    df.loc[index,col] = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Python    190\n",
       "En        200\n",
       "Math      194\n",
       "Physic    189\n",
       "Chem      181\n",
       "dtype: int64"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Python</th>\n",
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       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>82.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>125.0</td>\n",
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       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>4.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>56.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90.0</td>\n",
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       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>47.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>38.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>75.0</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "     Python     En   Math  Physic   Chem\n",
       "100    82.0   89.0   99.0   101.0  125.0\n",
       "101     4.0   31.0  109.0    32.0    5.0\n",
       "102    56.0  103.0   56.0     NaN   90.0\n",
       "103    47.0  100.0  147.0   138.0   99.0\n",
       "104    38.0   46.0    NaN    75.0   44.0"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
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       "      <th>2095</th>\n",
       "      <td>26.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2096</th>\n",
       "      <td>NaN</td>\n",
       "      <td>47.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>66.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2097</th>\n",
       "      <td>5.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>104.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2098</th>\n",
       "      <td>102.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>119.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2099</th>\n",
       "      <td>97.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Python    En  Math  Physic   Chem\n",
       "2095    26.0  59.0   8.0    54.0  149.0\n",
       "2096     NaN  47.0  90.0    92.0   66.0\n",
       "2097     5.0  97.0  73.0   140.0  104.0\n",
       "2098   102.0   6.0   7.0     5.0  119.0\n",
       "2099    97.0  19.0  77.0     NaN   48.0"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 82.,   4.,  56.,  47.,  38.,  18.,   3.,  35.,  86.,  19.,  76.,\n",
       "        31.,  64.,  72.,  55.,  96.,  63.,  28.,  85., 109.,   2., 110.,\n",
       "        70.,  51.,   6.,  65.,  24.,  48.,  44.,  11., 114., 129.,  87.,\n",
       "       108., 125.,  nan, 140., 132.,  91.,  34.,  54.,  30.,  12.,  98.,\n",
       "       142.,  79.,  13.,  77.,  40., 139.,  39.,  81., 112.,  36.,  22.,\n",
       "         5., 120.,  17., 127., 119.,  59., 146.,  89., 103.,   8.,  97.,\n",
       "       130.,  73.,  83., 122.,  95., 100.,  41.,  21., 136.,  80., 101.,\n",
       "        50.,  27.,  71.,  16., 141., 126., 102., 145.,  15.,  52.,  94.,\n",
       "        10.,  33., 137.,   9., 128.,  88.,  26.,  84.,  93.,   1.,   7.,\n",
       "       131., 107., 148.,   0., 105.,  66.,  32., 115., 118.,  58.,  53.,\n",
       "        29.,  42.,  57.,  62.,  25.,  60.,  69., 133.,  68.,  20., 106.,\n",
       "       147.,  78.,  90., 124., 149.,  92.,  75., 117., 143.,  99.,  37.,\n",
       "       123.,  45.,  61., 121., 135., 138., 116.,  14., 104.,  74.,  46.,\n",
       "       111.,  23.,  43.,  49., 144., 113.,  67., 134.])"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 去重之后的数据\n",
    "df['Python'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "143.0    20\n",
       "136.0    20\n",
       "102.0    19\n",
       "105.0    19\n",
       "26.0     19\n",
       "69.0     19\n",
       "31.0     18\n",
       "148.0    18\n",
       "75.0     18\n",
       "139.0    18\n",
       "1.0      18\n",
       "35.0     17\n",
       "140.0    17\n",
       "110.0    17\n",
       "125.0    17\n",
       "146.0    17\n",
       "141.0    17\n",
       "64.0     16\n",
       "30.0     16\n",
       "79.0     16\n",
       "73.0     16\n",
       "40.0     16\n",
       "10.0     15\n",
       "6.0      15\n",
       "65.0     15\n",
       "81.0     15\n",
       "28.0     15\n",
       "48.0     15\n",
       "92.0     15\n",
       "103.0    15\n",
       "         ..\n",
       "104.0     9\n",
       "12.0      9\n",
       "116.0     9\n",
       "13.0      9\n",
       "59.0      9\n",
       "93.0      9\n",
       "124.0     9\n",
       "85.0      8\n",
       "135.0     8\n",
       "131.0     8\n",
       "68.0      8\n",
       "66.0      8\n",
       "62.0      8\n",
       "120.0     8\n",
       "17.0      8\n",
       "25.0      8\n",
       "145.0     7\n",
       "58.0      7\n",
       "134.0     7\n",
       "113.0     7\n",
       "123.0     7\n",
       "39.0      7\n",
       "34.0      7\n",
       "43.0      7\n",
       "74.0      6\n",
       "144.0     6\n",
       "132.0     6\n",
       "142.0     5\n",
       "67.0      5\n",
       "49.0      5\n",
       "Name: Python, Length: 150, dtype: int64"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Python'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8.0      21\n",
       "96.0     19\n",
       "118.0    19\n",
       "24.0     19\n",
       "43.0     19\n",
       "27.0     19\n",
       "19.0     19\n",
       "41.0     18\n",
       "0.0      18\n",
       "3.0      18\n",
       "52.0     18\n",
       "4.0      17\n",
       "137.0    17\n",
       "1.0      17\n",
       "101.0    17\n",
       "51.0     17\n",
       "39.0     17\n",
       "100.0    17\n",
       "127.0    17\n",
       "115.0    16\n",
       "33.0     16\n",
       "112.0    16\n",
       "92.0     16\n",
       "126.0    16\n",
       "133.0    15\n",
       "32.0     15\n",
       "89.0     15\n",
       "95.0     15\n",
       "36.0     15\n",
       "93.0     15\n",
       "         ..\n",
       "12.0      9\n",
       "28.0      9\n",
       "106.0     9\n",
       "45.0      9\n",
       "80.0      9\n",
       "84.0      9\n",
       "58.0      9\n",
       "79.0      9\n",
       "71.0      9\n",
       "83.0      9\n",
       "142.0     9\n",
       "7.0       9\n",
       "6.0       8\n",
       "61.0      8\n",
       "149.0     8\n",
       "34.0      8\n",
       "20.0      8\n",
       "38.0      8\n",
       "130.0     8\n",
       "104.0     7\n",
       "120.0     7\n",
       "56.0      7\n",
       "146.0     7\n",
       "98.0      7\n",
       "134.0     6\n",
       "123.0     6\n",
       "35.0      6\n",
       "87.0      5\n",
       "42.0      5\n",
       "119.0     4\n",
       "Name: En, Length: 150, dtype: int64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "en = df['En'].value_counts()\n",
    "en"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8.0"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "en.index[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Python    75.0\n",
      "En        74.0\n",
      "Math      77.5\n",
      "Physic    73.0\n",
      "Chem      72.0\n",
      "dtype: float64 <class 'pandas.core.series.Series'>\n"
     ]
    }
   ],
   "source": [
    "s = df.median()\n",
    "print(s,type(s))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "zhongshu = []\n",
    "for col in df.columns:\n",
    "    zhongshu.append(df[col].value_counts().index[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Python    143.0\n",
       "En          8.0\n",
       "Math       80.0\n",
       "Physic     31.0\n",
       "Chem      125.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = Series(zhongshu,index = df.columns)\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Python</th>\n",
       "      <th>En</th>\n",
       "      <th>Math</th>\n",
       "      <th>Physic</th>\n",
       "      <th>Chem</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>82.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>4.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>56.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>47.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>38.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>18.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>126.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>56.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>139.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>3.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>144.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>35.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>63.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>86.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>19.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>76.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>31.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>119.0</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>64.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>72.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>55.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>96.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>146.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>63.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>89.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>28.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>125.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>74.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>85.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>109.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>39.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>2.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>65.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>110.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>57.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>109.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>71.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>70.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>134.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>121.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>51.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>43.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>6.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>105.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>65.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>4.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>119.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>24.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>139.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2070</th>\n",
       "      <td>127.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2071</th>\n",
       "      <td>93.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2072</th>\n",
       "      <td>116.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>61.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2073</th>\n",
       "      <td>4.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2074</th>\n",
       "      <td>143.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2075</th>\n",
       "      <td>46.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>113.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2076</th>\n",
       "      <td>143.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2077</th>\n",
       "      <td>143.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>119.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2078</th>\n",
       "      <td>84.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2079</th>\n",
       "      <td>95.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>84.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2080</th>\n",
       "      <td>124.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2081</th>\n",
       "      <td>26.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>149.0</td>\n",
       "      <td>145.0</td>\n",
       "      <td>127.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2082</th>\n",
       "      <td>19.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>89.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2083</th>\n",
       "      <td>84.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2084</th>\n",
       "      <td>28.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>105.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>89.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2085</th>\n",
       "      <td>23.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>88.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2086</th>\n",
       "      <td>86.0</td>\n",
       "      <td>133.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>125.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2087</th>\n",
       "      <td>21.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2088</th>\n",
       "      <td>20.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>37.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2089</th>\n",
       "      <td>96.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>64.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2090</th>\n",
       "      <td>22.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2091</th>\n",
       "      <td>16.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>58.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2092</th>\n",
       "      <td>65.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2093</th>\n",
       "      <td>69.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>58.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2094</th>\n",
       "      <td>128.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2095</th>\n",
       "      <td>26.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2096</th>\n",
       "      <td>143.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>66.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2097</th>\n",
       "      <td>5.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>104.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2098</th>\n",
       "      <td>102.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>119.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2099</th>\n",
       "      <td>97.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>48.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2000 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Python     En   Math  Physic   Chem\n",
       "100     82.0   89.0   99.0   101.0  125.0\n",
       "101      4.0   31.0  109.0    32.0    5.0\n",
       "102     56.0  103.0   56.0    31.0   90.0\n",
       "103     47.0  100.0  147.0   138.0   99.0\n",
       "104     38.0   46.0   80.0    75.0   44.0\n",
       "105     18.0   11.0  122.0     3.0  126.0\n",
       "106     56.0   26.0  106.0    14.0  139.0\n",
       "107      3.0  137.0   75.0    67.0  144.0\n",
       "108     35.0   47.0  102.0    60.0   63.0\n",
       "109     86.0  126.0   80.0    88.0  149.0\n",
       "110     19.0  140.0   80.0    35.0   33.0\n",
       "111     76.0    8.0    5.0    11.0   33.0\n",
       "112     31.0   54.0   91.0   119.0   69.0\n",
       "113     64.0   37.0   50.0    23.0   21.0\n",
       "114     72.0   57.0  138.0    15.0   21.0\n",
       "115     55.0  120.0  104.0    32.0   25.0\n",
       "116     96.0   24.0   89.0    31.0  146.0\n",
       "117     63.0    8.0    8.0    64.0   89.0\n",
       "118     28.0    8.0  125.0    82.0   74.0\n",
       "119     85.0   39.0   70.0   132.0  111.0\n",
       "120    109.0   90.0   80.0    74.0   39.0\n",
       "121      2.0    8.0  103.0   114.0   65.0\n",
       "122    110.0   29.0   99.0    80.0   57.0\n",
       "123    109.0   88.0   81.0   135.0   71.0\n",
       "124     70.0  103.0  134.0   121.0  121.0\n",
       "125     51.0   92.0  117.0    31.0   43.0\n",
       "126      6.0   92.0   97.0    59.0  105.0\n",
       "127     65.0   90.0   52.0   148.0   22.0\n",
       "128      4.0  129.0   17.0   119.0   13.0\n",
       "129     24.0  100.0  107.0    28.0  139.0\n",
       "...      ...    ...    ...     ...    ...\n",
       "2070   127.0   77.0   24.0    16.0  125.0\n",
       "2071    93.0   61.0    9.0    28.0   22.0\n",
       "2072   116.0   61.0   54.0     8.0   61.0\n",
       "2073     4.0   72.0  140.0    31.0   34.0\n",
       "2074   143.0  108.0  123.0    32.0   33.0\n",
       "2075    46.0    8.0  135.0   124.0  113.0\n",
       "2076   143.0   18.0  136.0    38.0  125.0\n",
       "2077   143.0   11.0  129.0    54.0  119.0\n",
       "2078    84.0   55.0  129.0    37.0   87.0\n",
       "2079    95.0   50.0   45.0    19.0   84.0\n",
       "2080   124.0   74.0   65.0    31.0   53.0\n",
       "2081    26.0   35.0  149.0   145.0  127.0\n",
       "2082    19.0   21.0  101.0     3.0   89.0\n",
       "2083    84.0    8.0  131.0    71.0    4.0\n",
       "2084    28.0   74.0  105.0    68.0   89.0\n",
       "2085    23.0   93.0   84.0    97.0   88.0\n",
       "2086    86.0  133.0   26.0   125.0   13.0\n",
       "2087    21.0  124.0   40.0    31.0    5.0\n",
       "2088    20.0   15.0   35.0    31.0   37.0\n",
       "2089    96.0  123.0  123.0     5.0   64.0\n",
       "2090    22.0   43.0   92.0    78.0   60.0\n",
       "2091    16.0   31.0   17.0    60.0   58.0\n",
       "2092    65.0   18.0   13.0    13.0   34.0\n",
       "2093    69.0   49.0  109.0    40.0   58.0\n",
       "2094   128.0   46.0   10.0    82.0  111.0\n",
       "2095    26.0   59.0    8.0    54.0  149.0\n",
       "2096   143.0   47.0   90.0    92.0   66.0\n",
       "2097     5.0   97.0   73.0   140.0  104.0\n",
       "2098   102.0    6.0    7.0     5.0  119.0\n",
       "2099    97.0   19.0   77.0    31.0   48.0\n",
       "\n",
       "[2000 rows x 5 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = df.fillna(s)\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Python    0\n",
       "En        0\n",
       "Math      0\n",
       "Physic    0\n",
       "Chem      0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Python    190\n",
       "En        200\n",
       "Math      194\n",
       "Physic    189\n",
       "Chem      181\n",
       "dtype: int64"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Python</th>\n",
       "      <th>En</th>\n",
       "      <th>Math</th>\n",
       "      <th>Physic</th>\n",
       "      <th>Chem</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>82.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>4.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>56.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>47.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>38.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>75.0</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>18.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>126.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>56.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>139.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>3.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>144.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>35.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>63.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>86.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>88.0</td>\n",
       "      <td>149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>19.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>76.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>31.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>119.0</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>64.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>72.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>55.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>96.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>146.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>63.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>89.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>28.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>125.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>74.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>85.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>111.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Python     En   Math  Physic   Chem\n",
       "100    82.0   89.0   99.0   101.0  125.0\n",
       "101     4.0   31.0  109.0    32.0    5.0\n",
       "102    56.0  103.0   56.0     NaN   90.0\n",
       "103    47.0  100.0  147.0   138.0   99.0\n",
       "104    38.0   46.0    NaN    75.0   44.0\n",
       "105    18.0   11.0  122.0     3.0  126.0\n",
       "106    56.0   26.0  106.0    14.0  139.0\n",
       "107     3.0  137.0   75.0    67.0  144.0\n",
       "108    35.0   47.0  102.0    60.0   63.0\n",
       "109    86.0  126.0    NaN    88.0  149.0\n",
       "110    19.0  140.0    NaN    35.0   33.0\n",
       "111    76.0    NaN    5.0    11.0   33.0\n",
       "112    31.0   54.0   91.0   119.0   69.0\n",
       "113    64.0   37.0   50.0    23.0   21.0\n",
       "114    72.0   57.0  138.0    15.0   21.0\n",
       "115    55.0  120.0  104.0    32.0   25.0\n",
       "116    96.0   24.0   89.0     NaN  146.0\n",
       "117    63.0    NaN    8.0    64.0   89.0\n",
       "118    28.0    NaN  125.0    82.0   74.0\n",
       "119    85.0   39.0   70.0   132.0  111.0"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3 = df.iloc[:20]\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Python</th>\n",
       "      <th>En</th>\n",
       "      <th>Math</th>\n",
       "      <th>Physic</th>\n",
       "      <th>Chem</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>82.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>4.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>56.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>47.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>38.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>18.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>126.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>56.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>139.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>3.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>144.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>35.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>63.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>86.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>19.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>76.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>31.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>119.0</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>64.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>72.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>55.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>96.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>146.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>63.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>89.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>28.0</td>\n",
       "      <td>125.0</td>\n",
       "      <td>125.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>74.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>85.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>111.0</td>\n",
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      ],
      "text/plain": [
       "     Python     En   Math  Physic   Chem\n",
       "100    82.0   89.0   99.0   101.0  125.0\n",
       "101     4.0   31.0  109.0    32.0    5.0\n",
       "102    56.0  103.0   56.0    90.0   90.0\n",
       "103    47.0  100.0  147.0   138.0   99.0\n",
       "104    38.0   46.0   75.0    75.0   44.0\n",
       "105    18.0   11.0  122.0     3.0  126.0\n",
       "106    56.0   26.0  106.0    14.0  139.0\n",
       "107     3.0  137.0   75.0    67.0  144.0\n",
       "108    35.0   47.0  102.0    60.0   63.0\n",
       "109    86.0  126.0   88.0    88.0  149.0\n",
       "110    19.0  140.0   35.0    35.0   33.0\n",
       "111    76.0    5.0    5.0    11.0   33.0\n",
       "112    31.0   54.0   91.0   119.0   69.0\n",
       "113    64.0   37.0   50.0    23.0   21.0\n",
       "114    72.0   57.0  138.0    15.0   21.0\n",
       "115    55.0  120.0  104.0    32.0   25.0\n",
       "116    96.0   24.0   89.0   146.0  146.0\n",
       "117    63.0    8.0    8.0    64.0   89.0\n",
       "118    28.0  125.0  125.0    82.0   74.0\n",
       "119    85.0   39.0   70.0   132.0  111.0"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''method : {'backfill', 'bfill', 'pad', 'ffill', None}, default None\n",
    "    Method to use for filling holes in reindexed Series\n",
    "    pad / ffill: propagate last valid observation forward to next valid\n",
    "    backfill / bfill: use NEXT valid observation to fill gap'''\n",
    "df3.fillna(method='bfill',axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2000, 5)"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#数据量足够大，空数据比较少，直接删除\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.dro"
   ]
  }
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